Magma read performance

Facundo Vozzi facundov79 at gmail.com
Fri Nov 26 19:35:55 UTC 2010


Thanks you Chris,
good to know that there is a real world magma application with 24 GB of
size.

See you,
Facu

On Fri, Nov 26, 2010 at 3:43 PM, Chris Muller <asqueaker at gmail.com> wrote:

> It's a proprietary data-aggregation tool that permutes every
> combination of data-attributes of an input-source at multiple levels.
> Even small inputs into the system can lead to very large output
> graphs.  It's a signature test-application for Magma; building and
> accessing a fairly large and complex data-structure and something I
> think would be very difficult to do, at least abstractly, with an
> RDBMS..
>
> On Thu, Nov 25, 2010 at 6:56 AM, Facundo Vozzi <facundov79 at gmail.com>
> wrote:
> > Hi Chris,
> > what kind of application is that? At work I'm working on a ten years old
> > production system with Oracle DBMS and it's 1 GB of size.
> >
> > Thanks for share your analysis again,
> > Facu
> > On Wed, Nov 24, 2010 at 2:38 PM, Chris Muller <ma.chris.m at gmail.com>
> wrote:
> >>
> >> There has been interest in Magma's read and query performance lately,
> >> so I thought I would share results of a recent benchmark test.
> >>
> >> It's an actual application which does very heavy reading and writing
> >> to a Magma repository.  This test was 24GB of repository work, over
> >> two days.  My goal was to determine, once the persistent model becomes
> >> many times the size of RAM and HD access appeared to become the
> >> limiting factor:
> >>
> >>  - how fast is Magma, in terms of "objects per second" and in
> >> "kilobytes per second"?
> >>  - how fast is this relative to the speed when the repository was empty?
> >>
> >> Conclusion:
> >>
> >>  - Magma started at 4K objects per second (empty repository), 282K per
> >> second.
> >>  - Finished with 2.3K objects per second (6GB repository), 750K per
> >> second.
> >>  - Memory consumption by the image never exceeded 300MB.
> >>
> >> It is important to note, these times are from the client MagmaSession
> >> point-of-view, including the full server roundtrip plus
> >> materialization.  Also, as can be seen from the attached data, there
> >> were many requests which only brought back one or two objects which,
> >> while dramatically lowering the overall reported throughput, is
> >> actually a real-world scenario for applications.
> >>
> >> Verbose description:
> >>
> >> When the test first started the repository was tiny, and there were
> >> only ~4K server requests during a 5-minute monitored period.  The
> >> total number of objects read across all ~4K requests was ~17M for an
> >> average throughput of 4K objects per second (ops).  As the model grew
> >> in size and complexity, more and more objects during the 5-minute
> >> monitored intervals were required to perform application-posting of
> >> the same number of input records; doubling to ~8K server requests
> >> during a 5-minute period, however only a few more objects brought back
> >> (total 21M), for an average of 2500 ops.  32 hours after that, the
> >> rate of reads dropped to about 2300 ops.  This is due to two factors:
> >>
> >>  - the objects were larger (e.g., more pointers to other objects)
> >>  - they were less clustered (having been replaced with objects which
> >> could not be co-located with the original object)
> >>
> >>
> >>
> >> The fact that objects got bigger (e.g., more pointers to other
> >> objects) is corroborated by another stat, "the number of *bytes* per
> >> second" read off the HD in order to access those objects.  Initially,
> >> when the test first started, there were about 4K *requests* for
> >> objects in one of the first five-minute periods, which were read at a
> >> rate of 282K per second.  24 hours later, there were only 2 times as
> >> many requests for objects, but were read-and-materialized at a rate of
> >> 750K bytes / second.
> >>
> >>
> >>  - Chris
> >>
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> >>
> >
> >
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